Visual Hand Movements for Machine ControL

نویسندگان

  • Sanjay Kumar
  • Dinesh Kant Kumar
  • Arun Sharma
چکیده

A new technique for automated classification of human hand gestures for robotics and computer control applications is presented. It uses view-based approach for representation, and statistical technique for classification. This approach uses a cumulative image-difference technique where the time between the sequences of images is implicitly captured in the representation of action. This results in the construction of Temporal History Templates (THTs). These THT’s are used to compute the 7 Hu image moments that are invariant to scale, rotation and translation. The recognition criterion is established using K-nearest neighbor (K-NN) mahalanobis distance. The preliminary experiments show that such a system can classify human hand gestures with a classification accuracy of 92%. Our research has been carried on in the robotics framework. The overall goal of our research is to test for accuracy of the recognition of hand gestures using this computationally inexpensive way of dimensionality-reduced representation of gestures for its suitability for robotics.

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تاریخ انتشار 2004